Appearance controls interpretation of orientation flows for 3D shape estimation

Steven Cholewiak 1 Romain Vergne 2 Benjamin Kunsberg 3 Steven Zucker 3 Roland Fleming 1, 3
1 Justus Liebig University Giessen [Germany]
2 MAVERICK - Models and Algorithms for Visualization and Rendering
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
3 YALE - Department of Computer Science
Abstract : The visual system can infer 3D shape from orientation flows arising from both texture and shading patterns. However, these two types of flows provide fundamentally different information about surface structure. Texture flows, when derived from distinct elements, mainly signal first-order features (surface slant), whereas shading flow orientations primarily relate to second-order surface properties (the change in surface slant). The source of an image's structure is inherently ambiguous, it is therefore crucial for the brain to identify whether flow patterns originate from texture or shading to correctly infer shape from a 2D image. One possible approach would be to use 'surface appearance' (e.g. smooth gradients vs. fine-scale texture) to distinguish texture from shading. However, the structure of the flow fields themselves may indicate whether a given flow is more likely due to first- or second-order shape information. We test these two possibilities in this set of experiments, looking at speeded and free responses
Keywords : Orientation Flows Shape from Shading Shape from Texture
Type de document :
Communication dans un congrès
Computational and Mathematical Models in Vision, May 2015, St. Pete Beach, Florida, United States
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https://hal.inria.fr/hal-01600027
Contributeur : Romain Vergne <>
Soumis le : lundi 2 octobre 2017 - 16:36:44
Dernière modification le : mercredi 11 avril 2018 - 01:58:12

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Steven Cholewiak, Romain Vergne, Benjamin Kunsberg, Steven Zucker, Roland Fleming. Appearance controls interpretation of orientation flows for 3D shape estimation. Computational and Mathematical Models in Vision, May 2015, St. Pete Beach, Florida, United States. 〈hal-01600027〉

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